Agentic AI-Powered HR Automation Instant CV Intelligence for Modern Hiring Teams Python + LangGraph + FastAPI

Agentic AI-Powered HR Automation
Instant CV Intelligence for Modern Hiring Teams
Python + LangGraph + FastAPI

🚀 Enterprise-grade Agentic AI platform for HR automation, candidate intelligence, and recruitment workflows.

For Anyone:
Interested In Learning Agentic AI for a real-world practical use-case

Automated CV review and candidate evaluation system using LangChain, LangGraph, LlamaIndex, FastAPI.
By AICampus - Agentic AI Research Community

🎯 Features

• ✅ Automated CV processing to Candidate Review & Evaluation
• 🤖 AI-powered data extraction (personal info, experience, skills, qualifications etc.)
• 📝 200-word professional summaries
• ⭐ Candidate scoring (1-100) with detailed reasoning
• 📊 Optional Google Sheets logging (configurable)
• 🚀 High-performance FastAPI with async support
• ⭐ Data Analytics with web-based HR Dashaboard support for management and visualization
• ⭐ Real-time notifications for HR teams

 

https://github.com/fanqingsong/agentic-ai-hr-automation-agent-python-langgraph-recruitment-workflow

Tech Features

• LangGraph workflows: (1) CV extraction — upload → extract → summary → save to MongoDB; (2) Job evaluation — extract job skills → evaluate candidate → skills match → score decision.
• AI-based data extraction (personal info, experience, skills) with structured JSON; minimal tokens via compact schemas.
• JWT authentication (PostgreSQL users, roles: job_seeker, hr_manager, admin).
• MinIO object storage for CV files; optional local fallback.
• Multi-LLM: OpenAI, Azure OpenAI, Anthropic Claude, Ollama (Qwen3 etc.).
• Error handling, timestamped records, health and config endpoints.

Automation Workflow

1. CV extraction workflow (single CV upload): upload_cv → extract_cv_data → generate_summary → save_candidate_to_mongodb.
2. Job evaluation workflow (score candidate for a job): extract_job_skills → evaluate_candidate → skills_match → score_decision.